Guide to email in Emacs using mu and mu4e

I get a lot of email. I’m also pretty sure you get a lot of email. However, email is still not a solved problemThis is evidenced by the fact that a quick Google search yields no less than ten viable options for email clients on my Mac. . Each potential email client is acceptable on it’s own, yet none of them satisfied all of my desired features:
This is evidenced by the fact that a quick Google search yields no less than ten viable options for email clients on my Mac.
The ability to access my email without an internet connectionI travel quite a lot, so this was very important to me. .
I travel quite a lot, so this was very important to me.
Easily move messages between different folders, which is how I keep all of my emails organized by project.
Quick yet powerful search of all my mail messages.
Having an


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A Look at Facebook’s Use of Systemd

At an event this month (you can find the video of it here), Davide Cavalca, a production engineer at Facebook, spoke about the growing adoption of systemd at the data centers of the company. From a report: Facebook continues making use of systemd’s many features inside their data centers. Some of their highlights for systemd use in 2018 includes: Facebook’s servers have been relying on systemd for about the past two years. Facebook is using CentOS 7 everywhere from hosts to containers. While relying on CentOS 7, Facebook backports a lot of packages including new systemd releases, Meson, other dependencies, and of course new Linux kernel releases. Facebook is working on “pystemd” as a Python (Cython) wrapper on top of SD-BUS.

Read more of this story at Slashdot.


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Amazon’s revamped Alexa app makes it easier to manage your smart home

Amazon’s Alexa app has just been given a major visual overhaul, largely focused on helping users set up and control their smart home. From the app’s new devices tab, users can view all their different Alexa-enabled devices and groups on one screen, as opposed to switching between tabs like before. And the app is much more colorful, too. Instead of a set white icons on a dark background, Alexa’s device groups – like Living Room, Kitchen, Bedroom, etc. – now feature colorful backgrounds, so you can find the one you need with just a glance.
An overhaul of the devices section was needed, not only for aesthetic reasons, but because Alexa owners are stocking their house with more than one smart device.
According to a Nielsen report on smart speaker adoption released earlier this month, 4 out of 10 U.S. smart speaker owners today have more than one device, for example. Smart


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How to build your own neural network from scratch in Python

Motivation: As part of my personal journey to gain a better understanding of Deep Learning, I’ve decided to build a Neural Network from scratch without a deep learning library like TensorFlow. I believe that understanding the inner workings of a Neural Network is important to any aspiring Data Scientist.This article contains what I’ve learned, and hopefully it’ll be useful for you as well!What’s a Neural Network?Most introductory texts to Neural Networks brings up brain analogies when describing them. Without delving into brain analogies, I find it easier to simply describe Neural Networks as a mathematical function that maps a given input to a desired output.Neural Networks consist of the following componentsAn input layer, xAn arbitrary amount of hidden layersAn output layer, ŷA set of weights and biases between each layer, W and bA choice of activation function for each hidden layer, σ. In this tutorial, we’ll use a Sigmoid activation function.The


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2080 RTX performance on Tensorflow with CUDA 10

Yes, they are great! The RTX 2080 Ti rivals the Titan V for performance with TensorFlow. The RTX 2080 seems to perform as well as the GTX 1080 Ti (although the RTX 2080 only has 8GB of memory).

Probably the most impressive new feature of the new NVIDIA RTX cards is their astounding Ray-Tracing performance. However, these are excellent cards for GPU accelerated computing. They are very well suited for Machine Learning workloads and having “Tensorcores” is nice.

I have just finished some quick testing using TensorFlow 1.10 built against CUDA 10.0 running on Ubuntu 18.04 with the NVIDIA 410.48 driver. These are preliminary results after spending only a few hours with the new RTX 2080 Ti and RTX 2080. I’ll be doing more testing in the coming weeks.
I’m not going to go over details of the new RTX cards, there are already plenty of posts on-line that cover that. I will


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